Former areas

Our research in wave–structure interaction is aimed at building the next generation of digital wave flumes: computational environments that can predict how marine and coastal structures behave under realistic, highly nonlinear wave loading, while remaining fast enough to support design, monitoring and decision-making. The broader vision is to bridge high-fidelity fluid–structure simulation, uncertainty quantification and machine learning so that wave loading is not treated as a single deterministic calculation, but as a rich prediction problem involving variability, sparse measurements and the need for rapid evaluation across many scenarios. This is particularly important for offshore, coastal and renewable-energy applications, where structures operate in uncertain environments and where reliable prediction of loads, response and risk is central to both safety and performance. 

Within this programme, our work spans both forward and inverse problems. On the forward side, we develop coupled numerical models that combine particle-based wave simulation with structural analysis and uncertainty propagation, enabling probabilistic prediction of structural response under breaking and non-breaking waves in representative flume settings. On the inverse side, we develop operator-learning methods that use sparse wave observations to recover structural loading, addressing the ill-posedness and non-uniqueness that arise when limited measurements are used to infer hidden forces. Taken together, these efforts contribute to a unified research agenda in which high-fidelity simulation provides the physical basis, uncertainty quantification characterises confidence and variability, and data-driven operators deliver the speed needed for surrogate modelling, sensing and digital twins in wave–structure interaction. 

The Achilles tendons are the primary tendons required for locomotion. The contraction of the gastrocnemius and soleus muscles result in a translational force through the Achilles tendon that results in downward motion of the foot away from the body. This is much necessary for actions like walking, running etc. During the motion, this provides both the elasticity and shock-absorption (visco-elasticity) to the foot. Despite being one of the strongest tendons in the body, it can undergo damage, known as tendonitis. About 30% of athletes undergo Achilles tendinopathy, with about 10% of yearly recurrence. While minor swelling can be treated easily, a rupture will require a surgery for treatment. Thus, comprehending motion in relation with fiber realignment and damage at the microstructural scales can enable.

Our work aims to couple three different scales: Skeleton scale (rigid-body-dynamics) with tendon scale (flexible-body elasticity) with microstructural changes (microscale damage at the fiber-matrix) to enable coupling real-world boundary conditions with the multiscale approach. The coupling of scales will enable to accurately calculate the realistic fiber alignment and thus better calculation of the stress concentrations for rupture modelling. The developed models will be validated and iterated with human foot experiments, done in collaboration with colleagues in Finland.